The “1024 Robot” can board and exit metro trains. Photos from Shenzhen Metro

An AI-driven logistics robot developed by a team led by He Zhijian, an assistant professor at the Shenzhen Technology University (SZTU) School of Artificial Intelligence in Pingshan District, has been deployed at Shenzhen Metro stations and has won an innovation award at the China Hi-tech Fair.

Named the “1024 Robot,” the system links warehouses, streets, the metro, and residential communities into a continuous logistics chain. It coordinates tasks ranging from merchant replenishment and central kitchen distribution to neighborhood commercial deliveries, all supported by an AI dispatch platform.

Designed for real-world operations, the robot can enter metro stations, pass through gates, use elevators, board and exit trains, and navigate complex environments using automatic obstacle avoidance and speed control. It targets time-sensitive deliveries such as courier parcels, fresh produce, and medicine, with a reported five-hour citywide delivery capability.

The system is built to address three major challenges faced by metro-area merchants: limited restocking time, insufficient storage space, and high labor costs. He noted that navigation and decision-making in these kinds of unstructured environments can be even more demanding than Level 4 (L4) autonomous driving for passenger vehicles.

The “1024 Robot” can use elevators.

He holds a Ph.D. from The Hong Kong Polytechnic University. Before joining SZTU in 2023, he served as a senior engineer at Huawei. He later founded the “1024 Robot” company, where he serves as both CEO and CTO.

He believes entrepreneurship based solely on academic papers is unrealistic. He emphasizes the need to deeply understand real industry demand and to focus on scalable, commercial production. As an applied research university designed to meet industrial needs, SZTU provided the environment that helped him both teach and start a business.

He trains students with practical, industry-oriented skills — from R&D and engineering design to supply chain management — with a goal of building robots that can operate commercially, not just serve as prototypes. He also notes that students can benefit from strong earning potential after graduation, provided they can endure intensive training.

Two of his students, Li Junwei and Zhang Yao, described their transition from classroom learning to product development. They tackled challenges including understanding CAN protocols, chassis control, simultaneous localization and mapping (SLAM), and deploying real-world navigation systems, solving problems through discussions with He.

Zhang said the experience reshaped his approach to learning. Rather than focusing only on grades, he learned to design products that can be reliably manufactured at scale, with attention to durability, cost control, and mass production. Zhang credited He with teaching him that the ultimate test of technology is whether it can solve real-world problems.